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Department of Economics, Uppsala University Working Paper Series, Department of Economics, Uppsala University

No 2015:6:
Estimation of DSGE models: Maximum Likelihood vs. Bayesian methods

Glenn Mickelsson ()

Abstract: DSGE models are typically estimated using Bayesian methods, but a researcher may want to estimate a DSGE model with full information maximum likelihood (FIML) so as to avoid the use of prior distributions. A very robust algorithm is needed to find the global maximum within the relevant parameter space. I suggest such an algorithm and show that it is possible to estimate the model of Smets and Wouters (2007) using FIML. Inference is carried out using stochastic bootstrapping techniques. Several FIML estimates turn out to be significantly diffrent from the Bayesian estimates and the reasons behind those differences are analyzed.

Keywords: Bayesian methods; Maximum likelihood; Business Cycles; Estimate DSGE models; (follow links to similar papers)

JEL-Codes: C11; E32; E32; E37; (follow links to similar papers)

51 pages, December 22, 2015

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